Fix precommit and undo changes to flashinfer_mla.py

Signed-off-by: Pavani Majety <pmajety@nvidia.com>

Author: pavanimajety

vllm/v1/attention/backends/flashinfer.py

@@ -1139,9 +1139,7 @@ def build(
                 "attention is available."
             )
             prefill_use_trtllm = True
-        decode_with_flashinfer_trtllm_api = (
-            causal and self.use_trtllm_decode_attention
-        )
+        decode_with_flashinfer_trtllm_api = causal and self.use_trtllm_decode_attention
 
         if not causal and self.use_dcp:
             raise NotImplementedError(
@@ -1242,10 +1240,7 @@ def build(
         # Compute paged_kv_indices if necessary
         # paged_kv_indices is only needed for FlashInfer native paths;
         # XQA/trtllm-gen paths use block_tables directly on GPU.
-        needs_native_paged_prefill = (
-            num_prefills > 0
-            and not prefill_use_trtllm
-        )
+        needs_native_paged_prefill = num_prefills > 0 and not prefill_use_trtllm
         needs_native_paged_decode = (
             num_decodes > 0 and not decode_with_flashinfer_trtllm_api
         )

vllm/v1/attention/backends/mla/flashinfer_mla.py

@@ -1,7 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
-from typing import TYPE_CHECKING, ClassVar
+from typing import ClassVar
 
 import torch
 from flashinfer.decode import trtllm_batch_decode_with_kv_cache_mla
@@ -25,10 +25,6 @@
 )
 from vllm.v1.attention.backends.utils import KVCacheLayoutType
 
-if TYPE_CHECKING:
-    from vllm.config import VllmConfig
-    from vllm.v1.kv_cache_interface import AttentionSpec
-
 logger = init_logger(__name__)
 
 FLASHINFER_MLA_WORKSPACE_BUFFER_SIZE = 128 * 1024 * 1024
@@ -56,22 +52,6 @@ class FlashInferMLAMetadataBuilder(MLACommonMetadataBuilder[MLACommonMetadata]):
     _cudagraph_support: ClassVar[AttentionCGSupport] = AttentionCGSupport.UNIFORM_BATCH
     query_len_support: ClassVar[QueryLenSupport] = QueryLenSupport.UNIFORM
 
-    def __init__(
-        self,
-        kv_cache_spec: "AttentionSpec",
-        layer_names: list[str],
-        vllm_config: "VllmConfig",
-        device: torch.device,
-    ) -> None:
-        super().__init__(
-            kv_cache_spec,
-            layer_names,
-            vllm_config,
-            device,
-            MLACommonMetadata,
-            supports_dcp_with_varlen=True,
-        )
-
 
 class FlashInferMLABackend(MLACommonBackend):
     supported_dtypes: ClassVar[list[torch.dtype]] = [torch.float16, torch.bfloat16]